mihailom-db commented on code in PR #45819:
URL: https://github.com/apache/spark/pull/45819#discussion_r1555542892
##########
sql/core/src/test/scala/org/apache/spark/sql/CollationSuite.scala:
##########
@@ -645,6 +646,34 @@ class CollationSuite extends DatasourceV2SQLBase with
AdaptiveSparkPlanHelper {
},
errorClass = "COLLATION_MISMATCH.IMPLICIT"
)
+
+ // check if substring passes through implicit collation
+ checkError(
+ exception = intercept[AnalysisException] {
+ sql(s"SELECT substr('a' COLLATE UNICODE, 0, 1) == substr('b' COLLATE
UNICODE_CI, 0, 1)")
+ },
+ errorClass = "COLLATION_MISMATCH.IMPLICIT"
+ )
+
+ checkAnswer(spark.sql("SELECT collation(:var1 || :var2)",
+ Map(
+ "var1" -> Literal.create("a", StringType(1)),
+ "var2" -> Literal.create("b", StringType(2))
+ )
+ ),
+ Seq(Row("UTF8_BINARY"))
+ )
+
+ withSQLConf(SqlApiConf.DEFAULT_COLLATION -> "UNICODE") {
+ checkAnswer(spark.sql("SELECT collation(:var1 || :var2)",
+ Map(
+ "var1" -> Literal.create("a", StringType(1)),
+ "var2" -> Literal.create("b", StringType(2))
+ )
+ ),
+ Seq(Row("UNICODE"))
+ )
+ }
Review Comment:
@srielau Is this the expected behaviour? Apparently we can pass different
collations to parameters. I understood that the behaviour should be if
StringType has priority of default then it has to have session level default
collation, as otherwise we might have different collations with same default
priority, which is not covered by design.
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